Day 723

Friday.

1408.3126
Using large scale structure to test multi field inflation
Ferraro, Smith

Primordial non-Gaussianity of local type is known to produce a scale-dependent contribution to the galaxy bias.  Several classes of multi-field inflationary models predict non-Gaussian bias which is stochastic, in the sense that dark matter and haloes don't trace each other perfectly on large scales.  In this work, forecast the ability of next-generation LSS surveys to constrain common types of primordial non-Gaussianity like f_NL, g_NL and tau_NL using halo bias, including stochastic contributions.  Provide fitting functions for statistical errors on these parameters which can be used for rapid forecasting or survey optimization.  A next-generation survey with volume V=25 Mpc^3/h^3, median redshift z=0.7 and mean bias b_g=2.5, can achieve sigma(f_NL)=6, sigma(g_NL)=1e5 and sigma(tau_NL)=1e3 if no mass information is available.  If halo masses are available, show that optimal weighting the halo field in order to reduce sample variance can achieve sigma(f_NL)=1.5, sigma(g_NL)=1e4 and sigma(tau_NL)=100 if haloes with mass down to M_min=1e11 Msun/h are resolved, outperforming Planck by a factor of 4 on f_NL and nearly an order of magnitude on g_NL and tau_NL.  Finally, study the effect of photometric redshift errors and discuss degeneracies between different non-Gaussian parameters, as well as the impact of marginalizing Gaussian bias and shot noise.